Environment variablesΒΆ

These are useful environment variables for usage and development in pfl:

  • PFL_NUMPY_DISTRIBUTE_METHOD - When using a NumPy-based model, use this environment variable to specify if TF or PyTorch should be used as distributed communication library. Valid values are {'tensorflow', 'pytorch'}.

  • PFL_PYTORCH_DEVICE - Manually override default device for Torch tensors. Valid values are {'cpu', 'cuda', 'mps'}. Prioritizes other devices than cpu by default.

  • PFL_WORKER_RANK, PFL_WORKER_ADDRESSES - used in distributed simulations with native TF/PyTorch distributed communication libraries, see Fast distributed simulations.